Final amendment: Ambiguous specification of EGFR mutations compounded by nil or negligible fragmented gene counts and erroneous application of the Kappa statistic reiterates doubts on the veracity of the TEP-study

Abstract

AbstractFinal amendment noteThis paper had raised two issues - the error-prone classification and mistaken application of the Kappa statistic. The classification critique still holds, and is being taken up with other criticisms at http://www.biorxiv.org/content/early/2017/07/02/146134. The Kappa statistic was an error on my part since I had failed to see another page in Table S1. Please consider this pre-print closed.Original abstractThe use of RNA-seq from tumor-educated platelets (TEP) as a ‘liquid biopsy’ source [1] has been refuted recently (http://biorxiv.org/content/early/2017/06/05/146134, not peer-reviewed). The TEP-study also mentioned that mutant epidermal growth factor receptor (EGFR) was ‘accurately distinguished using surrogate TEP mRNA profiles’, which is contested here. It is shown that only 10 out of 24 (a smaller sample set, original study has 60) non-small cell lung carcinoma (NSCLC) samples here has any expression at all. Even there the number of reads (101 bp) are [1, 4, 1, 14, 9, 1, 2, 19, 21, 6], and do not even add up to one complete EGFR gene (about 6000 bp). EGFR mutations have been painstakingly collated in www.mycancergenome.org/content/disease/lung-cancer/egfr. In stark contrast, the TEP study has no specification of the EGFR mutant used. The TEP study found EGFR mutations in 17/21 (81%), and EGFR wild-type in 4/39 (10%) for NSCLC samples (Table S7, reflected in Fig 3, Panel E in percentages). A major flaw is the assumption that a non “EGFR wild-type” is a “EGFR mutant” since cases zero with EGFR reads (which are almost half of the samples) could be either. The application of the Kappa statistic to this data is erroneous for two reasons. First, the Kappa statistic does not handle “unknowns”, as is the case for samples with zero expression. Secondly, ‘interobserver variation can be measured in any situation in which two or more independent observers are evaluating the same thing’ [2]. The 90% (Fig 3, Panel E) is just the percentage of samples (35/39) that are not “EGFT WT” in one observation. It is not qualified to be in the Kappa matrix, where it translates to 35, leading to a Kappa=0.707, which implies “substantial agreement” [2]. The other observation (looking for EGFR mutation) is in a different set. To summarize, this work reiterates negligible expression of EGFR reads in NSCLC samples, and finds serious shortcomings in the statistical analysis of subsequent mutational analysis from these reads in the TEP-study.